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Africa’s Turnaround
William MastersProfessor of Food Policy, Tufts University
http://nutrition.tufts.edu http://sites.tufts.edu/willmasters
From Crisis to Opportunity in African Agriculture*
* Forthcoming in Food and Financial Crises: Impacts on Sub-Saharan Africa, David R. Lee and Muna B. Ndulo. editors. Wallingford, UK: CAB International, 2011
Harambe Entrepreneur Alliance – Fourth Annual Symposium, 25 March 2011
How much longer?
Cartoon (c) 2002, reproduced with permission by Nicholson from "The Australian" newspaper: www.nicholsoncartoons.com.au
World agriculture is changing rapidlyMonthly average prices for wheat, maize and rice, Jan. 2000-Feb. 2011
Source: FAO Global Information and Early Warning System data (www.fao.org/giews/pricetool), downloaded Feb 20, 2011. All are monthly export prices, normalized to Jan. 2000=100, for US No. 2 Hard Red Winter Wheat, US No. 2 Yellow Maize, and Thai 100% Broken Rice.
1960/1961
1962/1963
1964/1965
1966/1967
1968/1969
1970/1971
1972/1973
1974/1975
1976/1977
1978/1979
1980/1981
1982/1983
1984/1985
1986/1987
1988/1989
1990/1991
1992/1993
1994/1995
1996/1997
1998/1999
2000/2001
2002/2003
2004/2005
2006/2007
2008/2009
2010/2011
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0
4.5Rest-of-WorldWorldSoutheast AsiaSouth AsiaSub-Saharan Africa
USDA estimates of average cereal grain yields (mt/ha), 1960-2010
Source: Calculated from USDA , PS&D data (www.fas.usda.gov/psdonline), downloaded 7 Nov 2010. Results shown are each region’s total production per harvested area in barley, corn, millet, mixed grains, oats, rice, rye, sorghum and wheat.
Africa’s green revolution is here
Cartoon (c) 2002, reproduced with permission by Nicholson from "The Australian" newspaper: www.nicholsoncartoons.com.au
Ruraldemography
Farm technologies
Food policies
Three big trends will change the picture
Rural population growth is a major causeof Africa’s impoverishment
Reprinted from Robert Eastwood, Michael Lipton and Andrew Newell (2010), “Farm Size”, chapter 65 in Prabhu Pingali and Robert Evenson, eds., Handbook of Agricultural Economics, Volume 4, Pages 3323-3397. Elsevier.
Rural demography • Food policies • Farm technologies
Land available per farm household (hectares)
1950
1955
1960
1965
1970
1975
1980
1985
1990
1995
2000
2005
2010
2015
2020
2025
2030
2035
2040
2045
2050
0
1,000,000
2,000,000
3,000,000
4,000,000
5,000,000
6,000,000
7,000,000
8,000,000
9,000,000
10,000,000
Total
Urban
Rural
1950
1955
1960
1965
1970
1975
1980
1985
1990
1995
2000
2005
2010
2015
2020
2025
2030
2035
2040
2045
2050
0.0
200,000.0
400,000.0
600,000.0
800,000.0
1,000,000.0
1,200,000.0
1,400,000.0
1,600,000.0
1,800,000.0
2,000,000.0
Total
Urban
Rural
Population by principal residence, 1950-2050
World (total) Sub-Saharan Africa
Source: Calculated from UN World Urbanization Prospects, 2009 Revision , released April 2010 at http://esa.un.org/unpd/wup. Downloaded 7 Nov. 2010.
2010
2010
Urban growth eventually employs all new workers
Rural demography • Food policies • Farm technologies
Until cities grow big enough, new workers have no choice but to be farmers
0
50
100
150
200
250
300
350
400 SS Africa
S Asia
SE Asia
Rest of World
Rural population estimates and projections, 1950-2030 Index1950=100
We are here:
≈480 m.
≈1.1 b.
≈310 m.
≈1.4 b.
Population
Source: Calculated from FAOStat (downloaded 17 March 2009). Rural population estimates and projections are based on UN Population Projections (2006 revision) and UN Urbanization Prospects (2001 revision).
Eventually land available per farmer rises
Rising rural populations reduce land available per farmer
Rural population by region, 1950-2050
Rural demography • Food policies • Farm technologies
Africa had the world’s fastest and longestrural population growth
-1.5%
-1.0%
-0.5%
0.0%
0.5%
1.0%
1.5%
2.0%
2.5%
SS Africa
S Asia
SE Asia
Rest of World
Rural population growth (decade averages), 1950-2030
Below zero = more land/farmer
Source: Calculated from FAOStat (downloaded 17 March 2009). Rural population estimates and projections are based on UN Population Projections (2006 revision) and UN Urbanization Prospects (2001 revision).
Rural population growth rates by region, 1950-2030
Rural demography • Food policies • Farm technologies
Over 2% annual growth for 30 years!
Under 1.3% annually, and falling
Africa also had the world’s fastest urban population growth
0.0%
1.0%
2.0%
3.0%
4.0%
5.0%
6.0%
SS Africa
S Asia
SE Asia
Rest of World
Urban population growth (decade averages), 1950-2030
Source: Calculated from FAOStat (downloaded 17 March 2009). Rural population estimates and projections are based on UN Population Projections (2006 revision) and UN Urbanization Prospects (2001 revision).
From >5% annually
…to <4%
Zero = no change
Urban population growth rates by region, 1950-2030
Rural demography • Food policies • Farm technologies
Africa’s long baby boom is finally entering the workforce
30
35
40
45
50
SS Africa
S Asia
SE Asia
Rest of World
Total dependency rates (ages 0-14 and 65+), 1950-2030
Source: Calculated from UN Population Projections, 2008 revision (March 2009), at http://esa.un.org/unpp.
Child and elderly dependency rates by region (0-15 and 65+), 1950-2030
Rural demography • Food policies • Farm technologies
Africa had the world’s most severe demographic burden (>45% )
now a demographic gift
Conclusions #1: Africa’s demographic turnaround
• Africa is just now emerging from the world’s most extreme demographic transition, which involved:– The world’s fastest rural population growth
> 2,0 % for 30 years, 1960s-1980s– The world’s fastest urban population growth
> 4,5 % for 50 years, 1950s-1990s– The worst dependency rates (children or the elderly)
> 45 % for 60 years, 1950 – 2010
• These pressures are now easing, steadily opening new windows of opportunity
Rural demography • Food policies • Farm technologies
Agricultural policy in Africa: 16 country studies*
Rural demography • Food policies • Farm technologies
*Plus five for cotton only
Methodology: Price distortions due to stroke of the pen policies
• Nominal Rate of Assistance:tariff-equivalent gap between
internal and foreign prices:
• Sometimes this is actually a tariff:
• Usually we observe only prices andmust infer marketing costs:
tNRA
fd PEmP **)1(
f
fd
P
PPNRA
Rural demography • Food policies • Farm technologies
Results: Heavy taxation of farmers and trade, followed by major reforms
Source: K.Anderson and W. Masters (eds), Distortions to Agricultural Incentives in Africa. Washington, DC: The World Bank, 2009.
Importable products
Exportable products
All farm products
This gap is anti-trade bias
This levelis netanti-farm bias
Rural demography • Food policies • Farm technologies
Individual countries follow varied pathsCountries’ total NRA for all tradable farm products, 1955-2004
Rural demography • Food policies • Farm technologies
Our common methodology allows comparison across all kinds of countries
No. of Percentage of world
countries Pop. GDP Ag.GDP
Africa 16 10 1 6
Asia 12 51 11 37
LAC 8 7 5 8
ECA 13 6 3 6
HIC 19 14 75 33
Total 68 91 95 90
Rural demography • Food policies • Farm technologies
The global context is becoming more favorable, as other countries limit their subsidies
Average NRAs for all products by year, with 95% confidence bands -1
01
2-1
01
2
1960 1970 1980 1990 2000
1960 1970 1980 1990 2000 1960 1970 1980 1990 2000
AFRICA ASIA (excl. Japan) ECA
HIC LAC
All Primary Products (incl. Nontradables)
Source: W.A. Masters and A. Garcia (2009), “Agricultural Price Distortion and Stabilization: Stylized Facts and Hypothesis Tests,” in K. Anderson, ed., Political Economy of Distortions to Agricultural Incentives. Washington, DC: World Bank.
Less anti-farm bias
Less pro-farm bias
Rural demography • Food policies • Farm technologies
-1
.0-0
.50
.00
.51
.01
.5
6 8 10 6 8 10
All Primary Products Tradables
All Primary Products Exportables Importables
NR
A
Income per capita (log)
National average NRAs by real income per capita, with 95% confidence bands
Source: Author’s calculations, from data available at www.worldbank.org/agdistortions. Each line shows data from 66 countries in each year from 1961 to 2005 (n=2520), smoothed with confidence intervals using Stata’s lpolyci at bandwidth 1 and degree 4. Income per capita is expressed in US$ at 2000 PPP prices.
(≈$22,000/yr)(≈$400/yr) (≈$3,000/yr)
≈$5,000/yr
Africa is not yet at the income levelsassociated with costly farm subsidies
Rural demography • Food policies • Farm technologies
• Policy reforms have finally cut Africa’s heavy colonial and post-colonial taxation of farmers– The average burden per farmer reached US$134 in the ‘70s
• Further reduction is possible and desirable– The average burden per farmer was US$41 in 2000-04,
– …more than all public investment or foreign aid to the sector
• Later, the challenge will be to limit subsidies– As incomes rise, political pressures shift rapidly
Conclusions #2: Africa’s food-policy turnaround
Rural demography • Food policies • Farm technologies
1960/1961
1962/1963
1964/1965
1966/1967
1968/1969
1970/1971
1972/1973
1974/1975
1976/1977
1978/1979
1980/1981
1982/1983
1984/1985
1986/1987
1988/1989
1990/1991
1992/1993
1994/1995
1996/1997
1998/1999
2000/2001
2002/2003
2004/2005
2006/2007
2008/2009
2010/2011
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0
4.5Rest-of-WorldWorldSoutheast AsiaSouth AsiaSub-Saharan Africa
USDA estimates of average cereal grain yields (mt/ha), 1960-2010
Source: Calculated from USDA , PS&D data (www.fas.usda.gov/psdonline), downloaded 7 Nov 2010. Results shown are each region’s total production per harvested area in barley, corn, millet, mixed grains, oats, rice, rye, sorghum and wheat.
What’s behind Africa’s green revolution?
Rural demography • Food policies • Farm technologies
African agriculture is really distinctive
Source: Reprinted from W.A. Masters, “Paying for Prosperity: How and Why to Invest in Agricultural Research and Development in Africa” (2005), Journal of International Affairs, 58(2): 35-64.
Rural demography • Food policies • Farm technologies
Appropriate new technologies have only recently been developed and disseminated
Source: Reprinted from W.A. Masters, “Paying for Prosperity: How and Why to Invest in Agricultural Research and Development in Africa” (2005), Journal of International Affairs, 58(2): 35-64.
Rural demography • Food policies • Farm technologies
Conclusions:Three turnarounds in African agriculture
• Rural demography– Slowdown in rural and urban population growth– Reduction in the dependency rate (children or elderly)
• Food policies – Many reforms done– More challenges ahead
• Farm technologies– Yields and output are rising– Technological transformation is finally under way
Rural demography • Food policies • Farm technologies
-
10
20
30
40
-
5
10
15
20
1975 1980 1985 1990 1995 2000 2005
Health AgricultureFood Aid Debt ReliefTotal ODA (right axis)
ODA commitments to Africa in selected sectors and total, 1973-2006(real US dollars per capita)
Source: Author's calculations, from OECD Development Assistance Committee (2008), Bilateral ODA commitments by Purpose (www.oecd.org/dac), deflated by OECD deflator (2005=100) and divided by midyear population estimates for Sub-Saharan Africa from the U.S. Census Bureau, International Database.
Reproduced from W.A. Masters (2008), “Beyond the Food Crisis: Trade, Aid and Innovation in African Agriculture.” African Technology Development Forum 5(1): 3-15.
Postscript: What role for foreigners in Africa’s turnaround?
Foreign aid to African agriculture had dropped
to US$1 per African(vs. US$4 for health,and US$38 in total).
From such a small base, rapid growth is possible
Rural demography • Food policies • Farm technologies